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Quantifying the Effects of Climate Variability and Change on Hydrologic Extremes in the Pacific Northwest. Alan F. Hamlet JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington. CBCCSP Research Team Lara Whitely Binder Pablo Carrasco

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slide1

Quantifying the Effects of Climate Variability and Change on Hydrologic Extremes in the Pacific Northwest

  • Alan F. Hamlet
  • JISAO/CSES Climate Impacts Group
  • Dept. of Civil and Environmental Engineering
  • University of Washington
slide2

CBCCSP Research Team

Lara Whitely Binder

Pablo Carrasco

Jeff Deems

Marketa McGuire Elsner

Alan F. Hamlet

Carrie Lee

Se-Yeun Lee

Dennis P. Lettenmaier

Jeremy Littell

Guillaume Mauger

Nate Mantua

Ed Miles

Kristian Mickelson

Philip W. Mote

Rob Norheim

Erin Rogers

Eric Salathé

Amy Snover

Ingrid Tohver

Andy Wood

http://www.hydro.washington.edu/2860/products/sites/r7climate/study_report/CBCCSP_chap1_intro_final.pdf

slide3

The Myth of Stationarity:

1) Climate Risks are stationary in time.

2) Observed streamflow records are the best estimate of future variability.

3) Systems and operational paradigms that are robust to past variability are robust to future variability.

slide4

The Myth of Stationarity Meets the Death of Stationarity

Muir Glacier in Alaska

Aug, 13, 1941

Aug, 31, 2004

Image Credit: National Snow and Ice Data Center, W. O. Field, B. F. Molnia

http://nsidc.org/data/glacier_photo/special_high_res.html

slide5

Why a Focus on Hydrologic Extremes?

Many human and natural systems are quite robust under “normal” conditions, but have the potential to be profoundly impacted by hydrologic extreme events.

slide7

Drought

Evacuated Reservoir During the 2001 PNW Drought

slide9

Low Flow and Temperature Impacts to Fish

Temperature/ Disease Related Fish Kill in the Klamath River in 2002

slide10

Dissolved Gas Management

Tailrace below Bonneville Dam

slide11

Dam Safety

Aftermath of the Johnstown Flood 1889

slide15

Nuts and Bolts:

Traditional Methods for Estimating Hydrologic Extremes

slide16

Step 1: Select Extreme Event from Each Historical Year

Streamflow (cfs)

Day of the Water Year (1 = Oct 1)

slide17

Step 2: Rank Extreme Events for All Years and Estimate Quantiles

1999

Streamflow (cfs)

Probability of Exceedance

slide18

Step 3: Fit a Probability Distribution to the Data

  • Examples of Commonly Used Probability Distributions:
  • Extreme Value Type 1 (EV 1)
  • Log Normal (LN)
  • Log Pearson
  • Generalized Extreme Value (GEV)
  • For climate change experiments, GEV is a good choice since the true nature of the future probability distributions is essentially unknown. However it turns out that the choice of distribution is not very critical in terms of the evaluating the sensitivity to warming and/or precipitation change.
slide19

Step 4: Estimate Extremes Associated with Return Intervals

Site Name Ret. Int. Flow (cfs)

SNOMO : 20 68660

SNOMO : 50 81332

SNOMO : 100 91145

Note that any return interval can be estimated. E.g. one could provide an estimate of the “5000 year flood”.

slide20

Step 5 (Optional) : Regionalize the Results

In order to avoid the inherent “noise” that comes with using imperfect site specific data, a common approach is to “regionalize” the results.

The idea is to pool as many sites as possible that have common hydroclimatic features (e.g. sites in western WA), and express the flood statistics as a simple ratio to the mean annual flood (MAF) averaged over many different basins.

E.g.

Q100 = 2.7 * MAF

This approach is used by Ecology in providing estimates of extreme events for the Dam Safety Program, for example.

slide21

Low flow analysis is essentially the same except we select the extreme low flow event from each year.

7Q10, for example, extracts the lowest 7-day running mean flow from each historical year, fits a probability distribution to the sequence of extremes, and selects the 90% exceedance value (i.e. a 10% probability of being at or below this extreme value)

slide22

Historical Perspectives:

Changing Flood Risk in the 20th Century

slide23

References:

Niemann, PJ, LJ Schick, FM Ralph, M Hughes, GA Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers, J. of Hydrometeorology, (in review)

Hamlet AF, Lettenmaier DP (2007) Effects of 20th century warming and climatevariability on flood risk in the western U.S. Water Resour Res, 43:W06427.doi:10.1029/2006WR005099

slide26

Role of Atmospheric Rivers in Flooding (Nov 7, 2006)

Niemann, PJ, LJ Schick, FM Ralph, M Hughes, GA Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers, J. of Hydrometeorology, (in review)

slide27

Role of Atmospheric Rivers in Flooding (Oct 20, 2003)

Niemann, PJ, LJ Schick, FM Ralph, M Hughes, GA Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers, J. of Hydrometeorology, (in review)

slide28

Niemann, PJ, LJ Schick, FM Ralph, M Hughes, GA Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers, J. of Hydrometeorology, (in review)

schematic of vic hydrologic model
Schematic of VIC Hydrologic Model
  • Sophisticated, fully distributed, physically based hydrologic model
  • Widely used globally in climate change applications
  • 1/16 Degree Resolution

(~5km x 6km or ~ 3mi x 4mi)

General Model Schematic

Snow Model

slide31

Evaluating the Hydrologic Model Simulations in the Context of Reproducing Flood Characteristics

Ln (X100 / Xmean) OBS

Avg WY Date of Flooding OBS

Avg WY Date of Flooding VIC

Ln (X100 / Xmean) VIC

Red = PNW, Blue = CA, Green = Colo, Black = GB

slide32

100-yr

Red = VIC

Blue = OBS

50-yr

X100 GEV flood/mean flood

20-yr

10-yr

5-yr

Zp

slide34

Detrended Temperature Driving Data for Flood Risk Experiments

“Pivot 2003” Data Set

Temperature

Historic temperature trend

in each calendar month

“Pivot 1915” Data Set

2003

1915

slide35

Simulated Changes in the 20-year Flood Associated with 20th Century Warming

DJF Avg Temp (C)

X20 2003 / X20 1915

DJF Avg Temp (C)

X20 2003 / X20 1915

X20 2003 / X20 1915

slide36

Schematic of a Cool Climate Flood

Precipitation

Produces Runoff

Precipitation

Produces Snow

Precipitation

Produces Snow

Snow

Snow

Freezing Level

Snow Melt

slide37

Schematic of a Warm Climate Flood

Precipitation

Produces Runoff

Precipitation

Produces Snow

Precipitation

Produces Snow

Snow

Snow

Snow Melt

Freezing Level

slide39

20-year Flood for “1973-2003” Compared to “1916-2003” for a Constant Late 20th Century Temperature Regime

DJF Avg Temp (C)

X20 ’73-’03 / X20 ’16-’03

X20 ’73-’03 / X20 ’16-’03

slide40

Summary of Flooding Impacts

Rain Dominant Basins:

Increases in flooding due to increased precipitation intensity, but no significant change from warming alone.

Mixed Rain and Snow Basins Along the Coast:

Strong increases due to warming and increased precipitation intensity (both effects increase flood risk)

Inland Snowmelt Dominant Basins:

Relatively small overall changes because effects of warming (decreased risks) and increased precipitation intensity (increased risks) are typically in the opposite directions.

slide42

X100 wENSO / X100 2003

X100 nENSO / X100 2003

X100 cENSO / X100 2003

DJF Avg Temp (C)

DJF Avg Temp (C)

DJF Avg Temp (C)

X100 wENSO / X100 2003

X100 nENSO / X100 2003

X100 cENSO / X100 2003

slide43

X100 wPDO / X100 2003

X100 nPDO / X100 2003

X100 cPDO / X100 2003

DJF Avg Temp (C)

DJF Avg Temp (C)

DJF Avg Temp (C)

X100 wPDO / X100 2003

X100 nPDO / X100 2003

X100 cPDO / X100 2003

slide45

21st Century Climate Impacts for the Pacific Northwest Region

Mote, P.W. and E. P. Salathe Jr., 2009: Future climate in the Pacific Northwest

slide46

Seasonal Precipitation Changes for the Pacific Northwest

http://cses.washington.edu/db/pdf/wacciach1scenarios642.pdf

slide47

HumanHealth

Infrastructure

Water Resources

Agriculture/Economics

A comprehensive climate change impacts assessment for Washington State

Coasts

Energy

Forest Resources

Salmon

Adaptation

the columbia basin climate change scenarios project
The Columbia Basin Climate Change Scenarios Project

297

Streamflow

Sites

This 3-year research project was designed to provide a comprehensive suite of 21st century hydroclimatological scenarios for the Columbia River basin and coastal drainages in OR and WA.

Collaborative Partners:

  • WA State Dept. of Ecology (via HB 2860)
  • Bonneville Power Administration
  • Northwest Power and Conservation Council
  • Oregon Water Resources Department
  • BC Ministry of the Environment
slide49

Columbia Basin Climate Change Scenarios Project

297 Sites

  • Smaller basins down to
  • ~500 km2
  • Monthly and daily streamflow time series
  • Assessment of hydrologic extremes
  • (e.g. Q100 and 7Q10)
available pnw scenarios
Available PNW Scenarios

2020s – mean 2010-2039; 2040s – mean 2030-2059; 2080s – mean 2070-2099

hybrid downscaling method
Hybrid Downscaling Method
  • Performed for each VIC grid cell:

Bias Corrected

Future

Monthly CDF

Hist. Daily

Timeseries

30 yr window

1916-2006

Projected Daily

Timeseries

Historic

Monthly CDF

Hist. Monthly

Timeseries

1916-2006

1970-1999

1916-2006

“Base Case”

slide53

Monthly to Daily Precipitation Scaling

SeaTac. Feb, 1996, hypothetical 30% Increase

Daily Precipitation (mm)

Day of Month

schematic of vic hydrologic model1
Schematic of VIC Hydrologic Model
  • Sophisticated, fully distributed, physically based hydrologic model
  • Widely used globally in climate change applications
  • 1/16 Degree Resolution

(~5km x 6km or ~ 3mi x 4mi)

General Model Schematic

Snow Model

slide55

Evaluation of Historical VIC Simulations for the Skagit River at Ross Dam

Blue—Observed Naturalized Flow

Red—Bias Adjusted VIC Simulations

Streamflow (cfs)

Streamflow (cfs)

slide58

Simulate Daily Time Step

Streamflow Scenarios

Associated with Changes

in Climate

Fit Probability Distributions

To Estimate Flood and Low Flow

Risks

Compare Flood

Risks to Those in the 20th Century

slide61

SNOMO

Streamflow (cfs)

Probability of Exceedance

2040s changes in flood risk snohomish at monroe
2040s Changes in Flood RiskSnohomish at Monroe

A1B

B1

10 Member Ensemble

Using the Hybrid Delta Downscaling Approach

Historical

slide63

2040s Changes in 7Q10Snohomish at Monroe

A1B

B1

10 Member Ensemble

Using the Hybrid Delta Downscaling Approach

Historical

slide66

Changes in High Flows

Q100 values are projected to systematically increase in many areas of the PNW due to increasing precipitation and rising snowlines.

http://www.hydro.washington.edu/2860/products/sites/r7climate/study_report/CBCCSP_chap7_extremes_final.pdf

slide67

Changes in Low Flows

7Q10 values are projected to systematically decline in many areas due to loss of snowpack and projected dryer summers

http://www.hydro.washington.edu/2860/products/sites/r7climate/study_report/CBCCSP_chap7_extremes_final.pdf

slide68

Current and Future Research

  • Additional VIC calibration to improve simulations, and comparison with DHSVM models (proposed)
  • Estimate the effects of reservoir management (in progress)
  • Incorporate more realistic effects to extreme precipitation from regional scale climate models (in progress)
  • Incorporate the effects of sea level rise and high flows on inundation using hydrodynamic modeling (proposed)
regional climate modeling at cig
Regional Climate Modeling at CIG
  • WRF Model (NOAH LSM) 36 to 12 km
    • ECHAM5 forcing
    • CCSM3 forcing (A1B and A2 scenarios)
  • HadRM 25 km
    • HadCM3 forcing
extreme precipitation
Extreme Precipitation

Change from 1970-2000 to 2030-2060 in the percentage of total precipitation occurring when daily precipitation exceeds the 20th century 95th percentile

larger increase on windward slopes of Cascades, Columbia basin

small increase or decrease along Cascade crest

slide73

Scenarios not forecasts!

The current projections are an initial attempt to provide quantitative estimates of the magnitude and direction of changing hydrologic extremes across the PNW, but there are many missing pieces:

More fully integrated modeling studies and summary products are needed to better support many policy and design decisions.

Reducing the cost and increasing the frequency of updates will help keep key products and data sets current.

slide76

Changing Sea Level Rise Projections

Nicholls, R. J. and Cazenave, A. (2010) Sea-Level Rise and Its Impact on Coastal Zones. Science 328, 1517-1520

slide77

We need to move forward now with the best available information.

We almost certainly will not have all of the data and projections that we would like to have before we have to make difficult decisions that materially affect future outcomes.

Identifying “No Regrets” strategies may be the best approach for coping with these realities.

slide78

An example of one idea that has been put forward for land use planning is the adoption of the “200 year flood” (0.5% probability of occurrence each year) as the standard for the FEMA flood insurance program and land use regulations.

One can argue that this is a “no regrets” strategy since flood impacts have been mounting over time due to ongoing development within the current Q100 boundaries, and flood risks are projected to increase substantially in many areas.

Are there specific geographic areas where such a policy would make more sense than others?